It’s not news that the world of big data analytics is expanding exponentially. The key to not only managing this tidal wave of data, but getting the most from it, will be the right tools. Microsoft has been working diligently to address the challenges of this new industry head-on with their new turnkey appliance—the Microsoft Analytics Platform System (APS). Emerging as one of the few vendors to embed in-database drivers for predictive analytics within Microsoft APS is Angoss Software.

Angoss’ in-database driver allows users to deploy predictive models directly within the appliance and unlock the value of big data. “Our end-to-end capability encompasses data acquisition, data preparation, and comprehensive modeling,” remarks Bill Sheldon, Chief Solutions Officer at Angoss. The company’s tools are designed to provide customers with an easy-to-use, end-to-end predictive analytics platform, with features like drag-and-drop functionality and automatic code generation. Furthermore, Angoss has the capability to integrate with multiple data sources and uses both structured and unstructured data, through a single data acquisition interface.

At the core of Angoss Software Suite is its unique, patented Decision Trees. This intuitive interface can be deployed directly to the Microsoft APS database, enabling faster response time when compared to traditional deployment approaches. For building predictive strategies that speak to the business user, Angoss also has Strategy Trees that combine the usability of Decision Trees with a visual and collaborative approach for strategy design, authoring and validating workflow. Strategy Trees combine customer segments, scores, business rules, and calculations to apply user-defined treatments and actions that support development of business strategies and optimization based on insights delivered through predictive analytics.

Angoss expertise expands much further than being solely a predictive analytics software provider.Through their professional services, Angoss helps clients quickly translate businesses issues into predictive models by providing their own subject matter expertise and experienced data scientists to provide training, knowledge transfer and mentoring and even model building as an augmentation to a clients own capabilities.

And for those organizations without the infrastructure,tools or skills in-house, Angoss provides turn-key, hosted managed services in specific industry verticals and functional applications. These two services give Angoss the ability to help any organization, regardless of size or resource, not just build models but execute on the insight gained from them.

Angoss prides itself on bridging the gap between data science and business users

A great example of this end-to-end capability is their recent work with a telecommunications firm based in the UK whose analytics strategy focused on external data sources and consultants to run their analytics platform. This inefficient and costly process led to deferred results and long turnaround times on any new activities or models. Angoss was able to come in and rapidly develop scorecards for the Telco’s different applications and products. “When they were signing a new customer for a new product, we were able to give the organization the ability to score the credit worthiness of the customer right at the time of acceptance,” says Sheldon. Angoss helped the client take advantage of transactional data, internal history, and additional demographic information to make more informed credit decisions. This lead to Angoss being able to identify $21 million of savings that was missed due to the client’s use of generic bureau scores as opposed to customized ones.

Angoss’ organizational capabilities and user friendly software, combined with its in-database predictive analytic capabilities with Microsoft’s APS, allows customers to better utilize the power of Big Data allowing them to collect, consolidate, analyze and ultimately see results in ways they can’t effectively do today.

Description A Microsoft partner specialized in easy-to-use predictive analytics and data mining tools, including in-database drivers for SQL and APS, that make it easier for clients to build and deploy predictive models that take advantage of Big Data.